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A Heterogeneous In-Memory Computing Cluster For Flexible End-to-End
  Inference of Real-World Deep Neural Networks

A Heterogeneous In-Memory Computing Cluster For Flexible End-to-End Inference of Real-World Deep Neural Networks

4 January 2022
Angelo Garofalo
G. Ottavi
Francesco Conti
G. Karunaratne
I. Boybat
Luca Benini
D. Rossi
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Papers citing "A Heterogeneous In-Memory Computing Cluster For Flexible End-to-End Inference of Real-World Deep Neural Networks"

1 / 1 papers shown
Title
AnalogNets: ML-HW Co-Design of Noise-robust TinyML Models and Always-On
  Analog Compute-in-Memory Accelerator
AnalogNets: ML-HW Co-Design of Noise-robust TinyML Models and Always-On Analog Compute-in-Memory Accelerator
Chuteng Zhou
F. García-Redondo
Julian Büchel
I. Boybat
Xavier Timoneda Comas
S. Nandakumar
Shidhartha Das
A. Sebastian
M. Le Gallo
P. Whatmough
25
16
0
10 Nov 2021
1